为什么导入在多处理中有成本？

Question

基本上，来自不同模块的进口越多，包括这些多处理任务所花费的时间越长，即使没有使用任何模块功能。每个进程都需要重新导入一切或什么？到底是怎么回事？

import time 

time1 = time.time() 

import multiprocessing as mp 
import numpy as np # Random imports (not used) 
import PIL 
import PySide 
import pandas 
# print time.time() - time1 # here this prints 0.0 

class Multi(object): 
    def __init__(self, queue): 
     self.q = queue  
    def run(self, a): 
     p = mp.Process(target=f, args=(a, q)) 
     p.start() 
     print self.q.get() 
     p.join() 


class MultiPool(object): 
    def __init__(self, N): 
     self.N = N 
     self.pool = mp.Pool(processes = self.N)  
    def run(self): 
     result = self.pool.map_async(f1, ((i,) for i in range(self.N))) 
     print result.get() 


def f(a, q): 
    for i in range(10000000): 
     b = i 
    q.put(b) 

def f1(a): 
    for i in range(10000000): 
     b = i 
    return b 

if __name__ == '__main__': 

    q = mp.Queue() 
    e = Multi(q) 

    # time1 = time.time() 
    print f1(0) 
    print time.time() - time1 

    time1 = time.time() 
    e.run('123') 
    print time.time() - time1 

    time1 = time.time() 
    mpool = MultiPool(2) 
    mpool.run() 
    print time.time() - time1 

# Output with random imports: 
>9999999 
>0.246000051498 
>9999999 
>0.693000078201 
>[9999999, 9999999] 
>0.720999956131 

# Output without imports: 
>9999999 
>0.246000051498 
>9999999 
>0.315999984741 
>[9999999, 9999999] 
>0.313999891281 

Answer 1

是multiprocessing必须在任何理线进口一切都只是因为有过程（新应用程序），而不是线程。

您将通过脚本测量的是执行方法的成本加上过程创建的成本。您可以测量进口成本，并且它们正好在import报表所在的位置执行。